Spoken Dialogue Systems SIG-AI Fall 2003 By: Sachin Kamboj.
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Transcript of Spoken Dialogue Systems SIG-AI Fall 2003 By: Sachin Kamboj.
Spoken Dialogue Systems
SIG-AI Fall 2003
By: Sachin Kamboj
Spoken Dialogue Systems October 6, 2003
Slide 2
Outline
Introduction to Spoken Dialogue Systems (SDS)
Applications of SDS
Components of SDS
Classification of SDSOn the basis of dialogue control
On the basis of initiative
On the basis of the verification strategy
Dialogue Manager Components
Challenges in the Design of an SDS
Speech Recognition
Language Understanding
Dialogue Manager
Response Generation
Speech Synthesis
Domain Specific Components
Spoken Dialogue Systems October 6, 2003
Slide 3
Introduction
Any computer system that interacts with a human using natural language.
Computer systems with which humans interact on a turn-by-turn basis and in which spoken natural language plays an important part in the communication. [Fraser 1997]
Spoken Dialogue Systems provide an interface between the user and a computer-based application that permits spoken interaction with the application in a relatively natural manner. [McTear 2002]
Spoken Dialogue Systems October 6, 2003
Slide 4
Applications
Automated reservation systemsCU Communicator System
TOOT
Mercury Flight Reservation System
NL email interfacesELVIS (EmaiL Voice Interactive System)
MailSec
Planning & Problem Solving Systems TRIPS & TRAINS
Circuit-Fix-It Shop System
Virtual Immersive Worlds (Steve)
Automated Banking Systems (Naunce)
Multimodal Information Systems (MATCH)
Spoken Dialogue Systems October 6, 2003
Slide 5
Components
Dialogue ManagerDialogue Manager
Speech RecognizerSpeech Recognizer Text-to-Speech System
Text-to-Speech System
Response GeneratorResponse GeneratorLanguage Understanding
Language Understanding
Domain SpecificComponents
Domain SpecificComponents
Spoken Dialogue Systems October 6, 2003
Slide 6
Speech Recognition
Involves the conversion of Spoken Sounds (user utterances) to Text (a string of words)
Requires knowledge of Phonetics and Phonology
Basic Idea:
Ŵ = argmaxw P(O/W) P(W)
Challenges:
Variability in speech signal due to the language, speaker and channel.
Handling continuous spontaneous speech.
Handling large vocabularies.
Providing a Speaker Independent Recognition System
Spoken Dialogue Systems October 6, 2003
Slide 7
Language Understanding
Converts a sequence of words into a Semantic Representation that can be used by the Dialogue Manager.
Involves the use of Morphology, Syntax and Semantics.
Example:
I want to fly to California
want(speaker, fly(_x, California))
Need robust parsing mechanisms to account for errors in speech recognition and ungrammatical utterances.
Spoken Dialogue Systems October 6, 2003
Slide 8
Dialogue Manager
“Manages” all the aspects of the dialogue.
It takes a semantic representation of the user’s utterance, figures out how the utterance fits in the overall context and creates a semantic representation of the systems response.
Performs all of the following:
Interprets the user's utterance within the current context.
Deal with malformed or unrecognized utterances.
Create a user model.
Perform grounding so that the user and the system have a common set of beliefs.
Manage initiative and system responses.
Handle issues of pragmatics in generation.
Spoken Dialogue Systems October 6, 2003
Slide 9
Response Generation
Involves constructing the message that is to be spoken to the user.
Requires the making of decision regarding:
What information should be included.
How the information should be structured.
The form of the messageThe choice of words
The syntactic structure
Current systems use simple methods such as the insertion of retrieved data into predefined slots in a template.
Spoken Dialogue Systems October 6, 2003
Slide 10
Speech Generation
Translates the message constructed by the response generation component into spoken form.
Two approaches may be used:
Prerecorded canned speech may be used with spaces to be filled by retrieved or previously recorded samples.
You have fifteen new emails.
Text-to-speech synthesis
Also known as concatenative speech synthesis.
Text-to-phoneme conversion. (spēch, d ī’əlộg’)
Phoneme-to-speech conversion.
Spoken Dialogue Systems October 6, 2003
Slide 11
Domain Specific Components
The dialogue manager usually needs to interface with some external software such as a database or an expert system.
The query or plans thus have to be converted from the internal representation used by the dialogue manager to the format used by the external domain specific system (e.g. SQL or STRIPS style goals).
This interfacing is handled by the domain specific components.
Spoken Dialogue Systems October 6, 2003
Slide 12
Classification of SDS
Based on the method used to control the dialogue with the user:
Finite state (or graph) based systems
Frame based systems
Agent based systems
Type of initiative
User Initiative
System Initiative
Mixed Initiative
Type of verification
Explicit Verification
Implicit Verification
Spoken Dialogue Systems October 6, 2003
Slide 13
Finite State Based Systems
The user is taken through a dialogue consisting of a sequence of predetermined steps or stages.
The dialogue flow is specified as a set of dialogue states with transitions denoting various alternative paths through the dialogue graph.
Get Destination
Get Destination
Verify Destination
Verify Destination
Get TravelDay
Get TravelDay
System: What is your destination?User: LondonSystem: Was that London?User: YesSystem: What day do you want to travel?User: FridaySystem: Was that Sunday?User: NoSystem: What day do you want to travel?
Verify Travel Day
Verify Travel Day
Spoken Dialogue Systems October 6, 2003
Slide 14
Finite State Based System (2)
Advantages:
Simple to construct
The required vocabulary and grammar for each state can be specified in advance
Results in more constrained speech recognition and language understanding.
Disadvantages:
Inhibits the user’s ability to ask questions and take initiative.
Do not allow over-informative answers.
Dialogues are not actually natural.
Example: Nuance demo banking system.
Spoken Dialogue Systems October 6, 2003
Slide 15
Frame Based System
User is asked questions that enable the system to fill slots in a template in order to perform tasks.
Dialogue flow is not predetermined but depends on:
the contents of the user’s input
the information that the system has to elicit.
System: What is your destination?User: LondonSystem: What day do you want to travel?User: Friday
System: What is your destination?User: London on Friday, October 10 around 9 in the morning.System: I have the following connection…
Destination City: London
Departure Day: Friday
Departure Date: October 10
Departure Time: 09 am
Spoken Dialogue Systems October 6, 2003
Slide 16
Frame Based Systems (2)
Act like rule-based systems, taking a particular action based on the current state of affairs.
Questions and other prompts that the system can ask should be listed along with conditions that have to be true for that particular question.
Advantages:
User can provide over-informative answers.
Allows more natural dialogues.
Disadvantages:
Cannot handle complex dialogues.
Range of applications limited to systems that elicit information from users and act on the basis of the same.
Example: Philips train timetable information system
Spoken Dialogue Systems October 6, 2003
Slide 17
Agent Based Systems
Allow complex communication between the system, the user and the underlying application in order to solve some problem or task.
Many variations depending on the application.
User: I’m looking for a job in the Calais area. Are there any server?
System: No, there aren’t any employment servers for Calais. However, there is an employment server for Pas-de-Calais and an employment server for Lille. Are you interested in one of these?
User: What time does the bank open?System: 9 am but they only accept job applications at noon.
User: What time does the bank open?System: 9 am but the guards come around 8.
Spoken Dialogue Systems October 6, 2003
Slide 18
Agent Based Systems (2)
Communication is viewed as interaction between two agents, each of which is capable of reasoning about its own actions and beliefs.
The dialogue model takes the preceding context into account
The dialogue evolves dynamically as a sequence of related steps that build on top of each other.
Advantages:
Allow natural dialogue in complex domains.
Disadvantage:
Such agents are usually very complex.
Hard to build.
Spoken Dialogue Systems October 6, 2003
Slide 19
Dialogue Manager Components
Dialogue Model: contains information about:Whether the system or the user should take the initiativeWhether explicit or implicit confirmation should be usedThe kind of speech acts that needs to be generated.
User Model: contain the systems beliefs about:What the user knowsThe user's expertise, experience and ability to understand the system's utterances.
Knowledge Base: contains information about the world and the domain.
Discourse Context: contains the dialogue history and current discourse.
Reference Resolver: performs reference resolution and handles ellipsis.
Plan Recognizer and Grounding Module: Interprets the user's utterance given the current contextReasons about the user's goals and beliefs.
Domain Reasoner/Planner: generates plans to achieve the shared goals.
Discourse Manager: manages the flow of information between all of the above modules.
Spoken Dialogue Systems October 6, 2003
Slide 20
Challenges in the Design of an SDS
Recovery from errors
Understanding pragmatically ill-formed utterances
Design of system prompts
Reference resolution
Understanding inter-sentential ellipsis
Plan recognition
Detection of conflicts
Performing grounding
And many more…
Spoken Dialogue Systems October 6, 2003
Slide 21
Recovery From Errors
A SDS should be able to detect errors or misunderstandings and recover from them.
Errors may be of the following types:
Uncertainties – speech recognition o/p has a low confidence score.
Inconsistencies – utterance conflicts with domain model/prev utterances
Ambiguities – more than one interpretation of a sentence
Luperfoy proposes a recovery strategy based on the following four stage algorithm:
Detection
Diagnosis (Classification of the error)
Repair plan selection
Interactive plan execution
Spoken Dialogue Systems October 6, 2003
Slide 22
Pragmatically Ill-formed Utterances
Listeners assume their beliefs of the world match the speaker’s
Hence, listeners interpret the utterances with respect to their beliefs
However, the speakers views of the world may differ from those of the listener:
As a result, the speakers utterance may be syntactically and semantically correct – yet violate the pragmatic rules.
Pragmatically Ill-formed utterances are of two types:
Extensional failuresHow many women on the UD wrestling team are CIS majors?
Intensional failuresWhich apartments are for sale?
What advanced placement courses did BOB take in high school?
What is Dr. Smith’s home address?
Spoken Dialogue Systems October 6, 2003
Slide 23
Design of System Prompts
Prompt design is important for:
Natural flowing conversations
To overcome shortcomings in speech recognition technology
One of the most challenging aspects is implicitly letting the user know what they can say. By not knowing:
Users can go beyond the functionality of the system
Not utilize the system as fully as they could
Prompt design is related to initiative
This is AZ Banking. How may I help you?
This is AZ banking. Say ‘check balance’ to check your balance, ‘pay bill’ to pay a bill or ‘transfer funds’ to transfer funds…
Prompts should be more explicit in the case of recognition errors and less explicit as the user shows greater familiarity with the system.
Spoken Dialogue Systems October 6, 2003
Slide 24
Reference Resolution
Reference is the process by which speakers use expressions like he and it to refer to entities salient in the discourse.
Reference resolution is the process of determining the referent entity of a referring expression.
For example:
John went to Bill’s car dealership to check out an Acura Integra. He looked at it for about an hour.
Before he bought it, John checked over the Integra very carefully.
Spoken Dialogue Systems October 6, 2003
Slide 25
Inter-sentential Ellipsis
Is the use of a syntactically incomplete sentence fragment, along with the context in which the fragment occurs, to communicate a complete thought and accomplish a speech act.
Examples:I want to cash this check. Small bills only please.
Speaker 1: Who are the candidates for the consultants?
Speaker 2: Mary Smith, Bob Jones and Ann Doe.
Speaker 1: Tom’s recommendations?
Spoken Dialogue Systems October 6, 2003
Slide 26
References
Carberry, Sandra: “Plan Recognition in Natural Language Dialogue”, ACL-MIT Press Series on Natural Language Processing, MIT Press, 1990.
Spoken Dialogue Systems October 6, 2003
Slide 27
Questions?